This indicator identifies high-volatility expansion phases by measuring the ratio between Bollinger Band deviation and ATR-adjusted volatility, while using linear regression slopes to determine trend direction.

Identifies high-probability breakout opportunities by monitoring the ratio between linear regression slopes and volatility-adjusted standard deviations.

This indicator identifies market compression by calculating the ratio between Bollinger Band volatility and Keltner Channel range against a linear regression trend line.

This indicator identifies high-probability breakout points by detecting price compression through a ratio of Bollinger Band deviation to ATR volatility combined with linear regression momentum.

This indicator identifies high-probability trend reversals by detecting periods of low volatility relative to linear regression price action.

This indicator identifies trend momentum using a custom linear regression slope while signaling potential volatility breakouts by comparing standard deviation against ATR-based price expansion.

This indicator identifies volatility compression and expansion by cross-referencing linear regression trends with a modified Bollinger Band squeeze metric.

This indicator identifies bullish and bearish trend momentum via linear regression analysis while flagging volatility squeezes using a ratio of standard deviation to adjusted ATR.

This indicator identifies trend reversals and volatility contractions by comparing linear regression slopes against a normalized standard deviation ratio.

This indicator identifies potential trend breakouts by calculating the ratio between Bollinger Band standard deviation and ATR-based volatility to detect price compression.

This indicator analyzes the relative expansion of Bollinger Band width against a linear weighted moving average to categorize market volatility states into actionable trading zones.

This indicator synthesizes Bollinger Band deviations with dual-period moving average differentials to visualize market momentum and directional trend shifts.

This indicator calculates a Bollinger Band variant by utilizing a Fibonacci-based deviation multiplier of 2.618 to project volatility extremes.

This indicator calculates a dynamic volatility channel by overlaying Fibonacci-based deviation multipliers onto a simple moving average to identify extreme price excursions.

This indicator calculates a Bollinger Band variant using the Golden Ratio (2.618) as the standard deviation multiplier to identify extreme price extensions.

This indicator calculates a dynamic trading envelope by determining the maximum squared deviation of the price range from a simple moving average to quantify extreme volatility.

This indicator identifies high-volatility expansion zones by calculating price deviations from moving averages while filtering for market compression using a Bollinger Squeeze logic.

This indicator calculates the divergence between fast and slow exponential moving averages and overlays Bollinger Bands to identify trend exhaustion and momentum shifts.

This indicator overlays a Bollinger Band envelope onto a MACD calculation to identify volatility-adjusted trend shifts and momentum extremes.

This indicator overlays Bollinger Bands onto a MACD calculation to identify trend reversals and price momentum exhaustion through standard deviation variance.

This indicator synthesizes MACD momentum with Bollinger Band volatility bounds to visualize directional shifts and price-action extremes.

This library provides custom functions to compute multi-method Bollinger Bands with precise deviation scaling alongside a dynamic MACD calculation for identifying price extremes and trend velocity.

This indicator calculates a MACD signal and applies Bollinger Band envelopes to the momentum values to identify trend exhaustion and volatility extremes.

This indicator identifies trend shifts by applying Bollinger Band volatility filters to the differential momentum of Exponential Moving Averages.

This indicator overlays Bollinger Bands onto a MACD calculation to identify momentum shifts and volatility-adjusted trend reversals.

This indicator overlays a Bollinger Band volatility envelope onto the MACD momentum oscillator to identify extreme price velocity and trend exhaustion points.

This indicator synthesizes an Oscillator-based Moving Average with a dynamic volatility envelope to identify trend momentum and structural reversals.

This indicator calculates a Relative Strength Index and overlays Bollinger Bands onto it to identify extreme momentum exhaustion zones.

This indicator identifies volatility compression by calculating the ratio between Bollinger Band deviation and Keltner Channel width while mapping price momentum via linear regression slopes.

This indicator identifies market volatility compression by comparing Keltner Channel width against Bollinger Band standard deviation while plotting linear regression slopes to detect directional momentum shifts.

This indicator utilizes a weighted price summation algorithm combined with an Exponential Moving Average crossover to identify trend momentum and directional shifts.

This indicator quantifies market sentiment by calculating the arithmetic distance between price extremes and a multi-period exponential moving average to visualize buying and selling pressure.

This indicator quantifies bearish pressure by measuring the vertical distance between the current low price and a smoothing exponential moving average.

This indicator quantifies market sentiment by measuring the aggregate deviation of high and low prices relative to a customizable moving average to determine bullish or bearish dominance.

This indicator quantifies bearish momentum by calculating the real-time divergence between the current price floor and a smoothed exponential moving average.

This indicator quantifies bearish momentum by calculating the negative divergence between current low prices and an exponential moving average, smoothed by a secondary simple moving average.

This indicator quantifies market dominance by calculating the average distance between price extremes and an Exponential Moving Average to visualize bullish or bearish momentum shifts.

This indicator plots two distinct Exponential Moving Average lines at periods of 144 and 169 to visualize long-term trend trajectories and structural price shifts.

This indicator synchronizes and plots Simple Moving Average values from M5, H1, and H4 timeframes onto a single chart to visualize cross- khung trend alignment.

This indicator synchronizes and plots moving average values from the H1 timeframe onto the current chart to visualize higher-level trend dynamics.

This indicator visualizes the synchronization of Simple Moving Averages across the M5, H1, and H4 timeframes to identify high-level trend alignment.

This indicator calculates and visualizes the dynamic variance between three distinct Simple Moving Average lengths (5, 10, and 15) across various higher timeframes to identify momentum shifts.